For organisations
Build AI capability around a real business priority.
NAI works with organisations to turn a defined capability gap into an executive learning journey built around workplace action and measurable evidence.
Discuss a corporate cohortHow it works
From capability gap to organisational evidence.
Diagnose
Name the capability gap, sponsor, cohort and success measure.
Shape
Configure learning, faculty, action project, data boundary and evidence plan.
Deliver
Run human-led learning with participant support and a governed workspace.
Evidence
Review workplace application, feedback, outcome signals and the next organisational decision.
Custom executive cohorts
A cohort shaped around one organisational priority.
Where it is commercially agreed, NAI can shape an intervention, typically six to twelve weeks, around a single priority your organisation has already decided matters.
The learning, the action project, the data boundary and the evidence plan are configured together with your sponsor, so what participants build is directly usable.
- A single agreed capability priority, not a generic curriculum
- A named sponsor and an agreed success measure
- A data boundary set before any participant work begins
- Evidence of workplace application, not attendance statistics
Data boundary
Sponsors see evidence. They do not see private learner work.
Participants work on real organisational challenges, so their capstone content can be commercially sensitive. That work is private to the participant by default.
Sharing anything with faculty, or marking work as ready for a sponsor, is an explicit choice the participant makes. Sponsor reporting is built on agreed metrics, progress and deliberately shared evidence, never on unrestricted access to participant notes.
This boundary is enforced in the database itself, not only in the interface.
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